volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for … model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility … EM-algorithm is developed for estimation. Each element of the vector return at time t is endowed with a common univariate …

We compared forecasts of stock market volatility based on real-time and revised …

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset … predictive performance relative to the standard volatility models. Furthermore, we construct volatility timing portfolios and …

between real estate and stock markets by fitting different classes of time-varying volatility model; second, to perform VaR … processes, in terms of mean, volatility, correlation, can be compared. In the econometric analyses, we estimate both a …

for volatility, correlation and covariance using high frequency financial data. It also implements complementary … paper first presents the issues associated with exploiting high frequency financial data. We then describe the volatility …

concentrate on modeling the conditional mean. However, financial time series exhibit certain stylized features such as volatility … to address this issue and to gain insights on the volatility patterns of CDS spreads, bond yield spreads and stock prices … creditworthiness of debtors more reliably. The obtained findings suggest that volatility takes a significant higher level in times of …

leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that … volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …We propose a methodology to include night volatility estimates in the day volatility modeling problem with high …